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In recent years, targeted therapy to treat cancer is gaining popularity. However, how to quantitatively and dynamically analyze the drug effect for molecularly targeted agents is quite different from traditional cytotoxic drugs. A novel preclinical model combining experimental methods and theoretical analysis is proposed to investigate the mechanisms of action and identify pharmacodynamic characteristic...
Optimal control policies for Markovian gene regulatory networks assume that external intervention is 100% specific to control genes. In practice, however, this effect may be unpredictable in the sense that intervention may also target alternative genes. Our goal is to find an optimal control policy that performs well in such cases. We model this by an uncertainty class of controlled networks corresponding...
Compressive imaging reconstructs the original signal by searching through the feasible space for the solution with maximum compactness under a known frame or dictionary. With the extent of available optimization tools, the recovery performance mainly relies on the power of dictionary to sparsely represent the data. Universal dictionaries can be trained from a corpus of natural images or they can be...
In cognitive radio, the spectrum sensing plays a key role in determining the performance of both the primary and the secondary networks. The eigenvalue based detection (EbD) algorithm has received broad attentions, since it shows significant robustness to the noise uncertainty problem. However, in EbD algorithm, it is quite difficult to obtain the distribution for the eigenvalues of the statistic...
In this paper, we consider two-way decode-and-forward (DF) multiple access and time division broadcasting relaying protocols with energy harvesting (EH) nodes. We propose optimal offline joint energy and transmission time allocation schemes for the considered relaying protocols taking into account channel state uncertainty. The proposed joint energy and transmission time allocation schemes are obtained...
We consider the problem of quickest localization of anomaly in a resource-constrained cyber network consisting of multiple components. Due to resource constraints, only one component can be probed at each time. The observations are random realizations drawn from two different distributions depending on whether the component is normal or anomalous. Components are assigned priorities. Components with...
In many network environments, a node seeks to expand the number of connections to other nodes who can make valuable transactions possible. In the possible presence of misbehaving nodes, who make harmful transactions possible, each (behaving) node must use discretion on whether to accept a prospective connection. We study this problem when the mechanism for expansion is an introduction-based reputation...
Biomarker discovery and classification in medical applications both typically involve feature selection applied to a small-sample high-dimensional dataset. Recent work has proposed a framework to integrate a prior over an uncertainty class of parameterized feature-label distributions with training data to obtain optimal classifiers, MMSE classifier error estimates, and evaluate the MSE of error estimates...
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